This project will examine multimodal atomic imaging approaches enabled by the most intense femtosecond and attosecond XFEL pulses. The results from these simulations will provide predictions and new concepts to guide multimodal measurements using XFEL, and at the same time, maximize use of limited LCLS-II resources.

The goal of this project is to use a comparative framework that includes three state-of-the-art colorectal cancer models. Funded under the National Cancer Institute’s (NCI) Cancer Intervention and Surveillance Modeling Network (CISNET) program, these colorectal cancer models were independently developed for the evaluation of interventions, with emphasis on screening, and describe colorectal cancer natural history using different underlying assumptions.

This project will employ advanced ab initio quantum many-body techniques coupled with applied mathematics and computer science methods to study a wide range of nuclei and to accurately describe the atomic nucleus from first principles.

Researchers from the Southern California Earthquake Center (SCEC) are working to enhance their earthquake simulation and hazard mapping tools to provide the best possible information in terms of earthquake ground motion and seismic hazard.

This project consists of developing and implementing a novel in silico drug design method coupling ML and physics-based methods.

Focusing on ceramic solid-state battery electrolytes and metal hydride hydrogen storage materials, this project integrates three sets of simulation capabilities to predict ion transport kinetics at interfaces.

This project establishes a progressive hierarchy of detailed simulation campaigns of internal combustion engines that will enable scientific discovery and development of predictive models for cycle-to-cycle variability.

This project aims to improve the accuracy and decrease the computational cost of computational methods for designing peptides and proteins for medical and manufacturing applications.

This project investigates how supersonic wall-bounded turbulent flows are affected by the thermal wall boundary condition and how they interact with flexible walls.

This project uses state-of-the-art radiation-hydrodynamics simulations to explore the full physics of supernova explosions.

This project aims to achieve ultrafast control of functional materials via confluence of leadership-scale quantum dynamics simulations, machine learning (ML) and cutting-edge x-ray free- electron laser (XFEL) experiments.

This INCITE project supports the Energy Exascale Earth System Model (E3SM) model, a multi-laboratory project developing a leading-edge climate and Earth system designed to address DOE mission needs.

This project is intended to advance the researchers' first-principles approach, based on real-time time-dependent density functional theory, so as to study electronic stopping processes of complex systems for which going beyond typical-linear response theory formalism is necessary.

Using large-scale simulations based on quantum mechanics, this project tackles two classes of problems: designing (i) sustainable materials to efficiently capture and convert solar energy, and (ii) materials to build novel, optically addressable quantum platforms, including quantum sensors.

The goal of this project is the prediction and understanding of quantum-mechanical properties of materials that display novel properties including novel quantum phases.

This project seeks study laser plasma interactions on meaningful spatial and temporal scales of relevance to various inertial fusion energy scenarios.

This project uses the gyrokinetic particle-in-cell code XGC to study fundamental edge physics issues critical to the success of ITER and the magnetic fusion energy programs.

This project combines a highly scalable computational fluid dynamics solver with anisotropically adapted unstructured grids to enable flow simulations of unprecedented scale and complexity on Theta, gaining insight into questions of 3D active flow control.

The team will use Theta to carry out simulations aimed at advancing the design of next-generation nuclear reactors. Their project will perform high-fidelity calculations of the flow and heat transfer behavior for pebble bed, gas-cooled reactors and force fluctuation in a fuel assembly with spacer grids.

This project will advance fusion energy research by performing large-scale simulations to shed light on plasma surface interactions. The team will use Theta to study the response of tungsten, the proposed ITER divertor, to low-energy, mixed H-He plasma exposure in the presence of impurity atoms.